Data Validation within a Data Set

Justin_SVU

I am hoping someone can point me in the right direction as I am spinning my wheels a bit on this one.

Scenario:

I have a snapshot of our employee population which is about 25,000 employees. In this spreadsheet there are about 50 columns 5 of which identify where in the organization you fall (Company, Region, Function, etc...). These are manually populated columns that are 95% accurate. You can determine the correct sorts by looking at someone's location, department, direct mgr, and 1st indirect mgr. I want Alteryx to look at this and be able to point out the 5% who don't look like the rest and give us it's best guess as to the proper value. This will allow us to improve our reporting and data integrity in our HRIS system.

Any help or guidance in the right direction would be appreciated. Currently, I have tried the predictive tools, but I am unsure if I am just using them wrong or that is the wrong route. I have watched videos on the predictive tools, but when I try with this spreadsheet it gets hung up around 20% and I'm not sure if that is user error or the large amount of data.

Thank you!

Claje

If I'm understanding this use case correctly, you're really looking for cases that match a pattern really well, and cases that don't match a pattern, so you can identify what to do with them.

At a very high level, I would recommend taking a look at the Fuzzy Match tool.  This tool can take some getting used to, but it can do things like see how close two strings are to one another, and provide confidence thresholds alongside this.  This will probably accomplish what you are looking for.